{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style('darkgrid')\n",
    "sns.set(font_scale=1.5)\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>school_rating</th>\n",
       "      <th>size</th>\n",
       "      <th>reduced_lunch</th>\n",
       "      <th>state_percentile_16</th>\n",
       "      <th>state_percentile_15</th>\n",
       "      <th>stu_teach_ratio</th>\n",
       "      <th>avg_score_15</th>\n",
       "      <th>avg_score_16</th>\n",
       "      <th>full_time_teachers</th>\n",
       "      <th>percent_black</th>\n",
       "      <th>percent_white</th>\n",
       "      <th>percent_asian</th>\n",
       "      <th>percent_hispanic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>341.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>341.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "      <td>347.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.968300</td>\n",
       "      <td>699.472622</td>\n",
       "      <td>50.279539</td>\n",
       "      <td>58.801729</td>\n",
       "      <td>58.249267</td>\n",
       "      <td>15.461671</td>\n",
       "      <td>57.004692</td>\n",
       "      <td>57.049856</td>\n",
       "      <td>44.939481</td>\n",
       "      <td>21.197983</td>\n",
       "      <td>61.673487</td>\n",
       "      <td>2.642651</td>\n",
       "      <td>11.164553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.690377</td>\n",
       "      <td>400.598636</td>\n",
       "      <td>25.480236</td>\n",
       "      <td>32.540747</td>\n",
       "      <td>32.702630</td>\n",
       "      <td>5.725170</td>\n",
       "      <td>26.696450</td>\n",
       "      <td>27.968974</td>\n",
       "      <td>22.053386</td>\n",
       "      <td>23.562538</td>\n",
       "      <td>27.274859</td>\n",
       "      <td>3.109629</td>\n",
       "      <td>12.030608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>53.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>4.700000</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.100000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.100000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>420.500000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>30.950000</td>\n",
       "      <td>27.100000</td>\n",
       "      <td>13.700000</td>\n",
       "      <td>37.600000</td>\n",
       "      <td>37.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>40.600000</td>\n",
       "      <td>0.750000</td>\n",
       "      <td>3.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>595.000000</td>\n",
       "      <td>51.000000</td>\n",
       "      <td>66.400000</td>\n",
       "      <td>65.800000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>61.800000</td>\n",
       "      <td>60.700000</td>\n",
       "      <td>40.000000</td>\n",
       "      <td>13.500000</td>\n",
       "      <td>68.700000</td>\n",
       "      <td>1.600000</td>\n",
       "      <td>6.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>851.000000</td>\n",
       "      <td>71.500000</td>\n",
       "      <td>88.000000</td>\n",
       "      <td>88.600000</td>\n",
       "      <td>16.700000</td>\n",
       "      <td>79.600000</td>\n",
       "      <td>80.250000</td>\n",
       "      <td>54.000000</td>\n",
       "      <td>28.350000</td>\n",
       "      <td>85.950000</td>\n",
       "      <td>3.100000</td>\n",
       "      <td>13.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.000000</td>\n",
       "      <td>2314.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>99.800000</td>\n",
       "      <td>99.800000</td>\n",
       "      <td>111.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>98.900000</td>\n",
       "      <td>140.000000</td>\n",
       "      <td>97.400000</td>\n",
       "      <td>99.700000</td>\n",
       "      <td>21.100000</td>\n",
       "      <td>65.200000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       school_rating         size  reduced_lunch  state_percentile_16  \\\n",
       "count     347.000000   347.000000     347.000000           347.000000   \n",
       "mean        2.968300   699.472622      50.279539            58.801729   \n",
       "std         1.690377   400.598636      25.480236            32.540747   \n",
       "min         0.000000    53.000000       2.000000             0.200000   \n",
       "25%         2.000000   420.500000      30.000000            30.950000   \n",
       "50%         3.000000   595.000000      51.000000            66.400000   \n",
       "75%         4.000000   851.000000      71.500000            88.000000   \n",
       "max         5.000000  2314.000000      98.000000            99.800000   \n",
       "\n",
       "       state_percentile_15  stu_teach_ratio  avg_score_15  avg_score_16  \\\n",
       "count           341.000000       347.000000    341.000000    347.000000   \n",
       "mean             58.249267        15.461671     57.004692     57.049856   \n",
       "std              32.702630         5.725170     26.696450     27.968974   \n",
       "min               0.600000         4.700000      1.500000      0.100000   \n",
       "25%              27.100000        13.700000     37.600000     37.000000   \n",
       "50%              65.800000        15.000000     61.800000     60.700000   \n",
       "75%              88.600000        16.700000     79.600000     80.250000   \n",
       "max              99.800000       111.000000     99.000000     98.900000   \n",
       "\n",
       "       full_time_teachers  percent_black  percent_white  percent_asian  \\\n",
       "count          347.000000     347.000000     347.000000     347.000000   \n",
       "mean            44.939481      21.197983      61.673487       2.642651   \n",
       "std             22.053386      23.562538      27.274859       3.109629   \n",
       "min              2.000000       0.000000       1.100000       0.000000   \n",
       "25%             30.000000       3.600000      40.600000       0.750000   \n",
       "50%             40.000000      13.500000      68.700000       1.600000   \n",
       "75%             54.000000      28.350000      85.950000       3.100000   \n",
       "max            140.000000      97.400000      99.700000      21.100000   \n",
       "\n",
       "       percent_hispanic  \n",
       "count        347.000000  \n",
       "mean          11.164553  \n",
       "std           12.030608  \n",
       "min            0.000000  \n",
       "25%            3.800000  \n",
       "50%            6.400000  \n",
       "75%           13.800000  \n",
       "max           65.200000  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read in TN middle school dataset from GitHub\n",
    "df = pd.read_csv('https://raw.githubusercontent.com/LearnDataSci/article-resources/master/Essential%20Statistics/middle_tn_schools.csv')\n",
    "\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"8\" halign=\"left\">reduced_lunch</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_rating</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.0</th>\n",
       "      <td>43.0</td>\n",
       "      <td>83.581395</td>\n",
       "      <td>8.813498</td>\n",
       "      <td>53.0</td>\n",
       "      <td>79.50</td>\n",
       "      <td>86.0</td>\n",
       "      <td>90.00</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>40.0</td>\n",
       "      <td>74.950000</td>\n",
       "      <td>11.644191</td>\n",
       "      <td>53.0</td>\n",
       "      <td>65.00</td>\n",
       "      <td>74.5</td>\n",
       "      <td>84.25</td>\n",
       "      <td>98.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>44.0</td>\n",
       "      <td>64.272727</td>\n",
       "      <td>11.956051</td>\n",
       "      <td>37.0</td>\n",
       "      <td>54.75</td>\n",
       "      <td>62.5</td>\n",
       "      <td>74.00</td>\n",
       "      <td>88.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>56.0</td>\n",
       "      <td>50.285714</td>\n",
       "      <td>13.550866</td>\n",
       "      <td>24.0</td>\n",
       "      <td>41.00</td>\n",
       "      <td>48.5</td>\n",
       "      <td>63.00</td>\n",
       "      <td>78.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>86.0</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>16.681092</td>\n",
       "      <td>4.0</td>\n",
       "      <td>30.00</td>\n",
       "      <td>41.5</td>\n",
       "      <td>50.00</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>78.0</td>\n",
       "      <td>21.602564</td>\n",
       "      <td>17.651268</td>\n",
       "      <td>2.0</td>\n",
       "      <td>8.00</td>\n",
       "      <td>19.0</td>\n",
       "      <td>29.75</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              reduced_lunch                                                  \\\n",
       "                      count       mean        std   min    25%   50%    75%   \n",
       "school_rating                                                                 \n",
       "0.0                    43.0  83.581395   8.813498  53.0  79.50  86.0  90.00   \n",
       "1.0                    40.0  74.950000  11.644191  53.0  65.00  74.5  84.25   \n",
       "2.0                    44.0  64.272727  11.956051  37.0  54.75  62.5  74.00   \n",
       "3.0                    56.0  50.285714  13.550866  24.0  41.00  48.5  63.00   \n",
       "4.0                    86.0  41.000000  16.681092   4.0  30.00  41.5  50.00   \n",
       "5.0                    78.0  21.602564  17.651268   2.0   8.00  19.0  29.75   \n",
       "\n",
       "                     \n",
       "                max  \n",
       "school_rating        \n",
       "0.0            98.0  \n",
       "1.0            98.0  \n",
       "2.0            88.0  \n",
       "3.0            78.0  \n",
       "4.0            87.0  \n",
       "5.0            87.0  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['reduced_lunch', 'school_rating']].groupby(['school_rating']).describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>reduced_lunch</th>\n",
       "      <th>school_rating</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>reduced_lunch</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.815757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>school_rating</th>\n",
       "      <td>-0.815757</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "               reduced_lunch  school_rating\n",
       "reduced_lunch       1.000000      -0.815757\n",
       "school_rating      -0.815757       1.000000"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# only view these two variables\n",
    "df[['reduced_lunch', 'school_rating']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x288231bfef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(14,8))\n",
    "\n",
    "ax.set_ylabel('school_rating')\n",
    "\n",
    "# boxplot with only these two variables\n",
    "_ = df[['reduced_lunch', 'school_rating']].boxplot(by='school_rating', figsize=(13,8), vert=False, sym='b.', ax=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x288274ba748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,8))\n",
    "_ = sns.regplot(data=df, x='reduced_lunch', y='school_rating')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x28825cf29e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create tabular correlation matrix\n",
    "corr = df.corr()\n",
    "_, ax = plt.subplots(figsize=(13,10)) \n",
    "\n",
    "# graph correlation matrix\n",
    "_ = sns.heatmap(corr, ax=ax,\n",
    "                xticklabels=corr.columns.values,\n",
    "                yticklabels=corr.columns.values,\n",
    "                cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
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